Estimating suspended sediment concentration in Yangtze River from Landsat-TM image

Tao Chen; Pingxiang Li; Liangpei Zhang; Lite Shi

doi:10.1117/12.654892

3 November 2005 Estimating suspended sediment concentration in Yangtze River from Landsat-TM image

Tao Chen, Pingxiang Li, Liangpei Zhang, Lite Shi

Proceedings Volume 6043, MIPPR 2005: SAR and Multispectral Image Processing; 604319 (2005) https://doi.org/10.1117/12.654892
Event: MIPPR 2005 SAR and Multispectral Image Processing, 2005, Wuhan, China

Abstract

Traditionally, suspended sediment concentration (S) has been measured by time-consuming and costly boat surveys which allow the accurate measurement of S for single points in space and time. Remote sensing from spaceborne sensors has proved to be a useful method to such surveys as it provides and instantaneous and synoptic view of sediments that would otherwise be unavailable. The key to success of remote sensing in such a role is to get the suitable relationship between S and remotely sensed spectral radiance (L). In this research, an estimation model of suspended sediments in Yangtze River is built by using spectral analysis based on some correlative researches. Firstly, we attempt to fit the relation curve between suspended sediments concentration and reflectance of water by using three widely used classical models. Land spectral experiment, which simulates the condition of Yangtze River, is carried out to estimate the parameters of three models. And then, we analyze the Landsat TM data by using the models and finally compare the results with the hydrological data for error quantitative analysis.

Citation Download Citation

Tao Chen, Pingxiang Li, Liangpei Zhang, and Lite Shi "Estimating suspended sediment concentration in Yangtze River from Landsat-TM image", Proc. SPIE 6043, MIPPR 2005: SAR and Multispectral Image Processing, 604319 (3 November 2005); https://doi.org/10.1117/12.654892

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available